Probabilistic, Prediction-Based Schedule Debugging for Autonomous Robot Office Couriers
KI '99 Proceedings of the 23rd Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Contingency Selection in Plan Generation
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Probabilistic State-Dependent Grammars for Plan Recognition
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
A Plan Manager for Multi-robot Systems
International Journal of Robotics Research
Journal of Artificial Intelligence Research
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In this paper, we argue that a shift is needed for plan-based architectures to support versatile, long-lived systems. Our hypothesis is that we need to integrate plan generation, plan analysis and plan adaptation within a wholesome framework that allow a seamless integration of planning and plan execution activities, i.e. that the architectural focus should move away from planning towards so-called plan management. We present, in this paper, a software framework for plan management, which is based on a novel plan representation. This representation has been designed so that the actual context of the execution is available at all times: what the robot is doing and-more importantly-why it is doing it. Our plan manager implementation is available as open source, and has already been used on three different live systems, on which it demonstrated its capabilities.